Imagining an AI powered future for employee benefits
Are multinationals ready for the technology-driven future?
It‘s the year 2032, and Rita has a new job. She opens her workplace’s digital wellbeing app to select her employee benefits (EB), and artificial intelligence-powered (AI) voice assistant, Sam, greets her.
First, Sam shows her a map highlighting a deal that would allow her to use a gym near her home where she works remotely, and another near her office. He recommends a lunchtime yoga session to help her reset following a long meeting scheduled in her work calendar.
Next, Sam suggests insurance options tailored to Rita’s stage of life. She chooses life insurance and critical illness cover, family dental cover, and a fitness app linked to her smartwatch which rewards her with points toward shopping vouchers when she exercises.
Sam asks about Rita’s goals, and she says she’s saving to buy a home. A financial wellbeing app is added to her benefits programme, which connects to her banking app and generates an interactive budget based on her spending patterns.
Next, Sam asks Rita a series of questions about her health, then books in a video call for later that day. The doctor uses her answers to help design Rita’s health plan, guided by Sam’s recommendations for her age, stage, and location. Rita shares an image of a mole that worries her with Sam, which is analysed then flagged for investigation within minutes.
Sam books her an appointment at a clinic which removes the mole, then sends her digital receipt straight to an insurance claims portal, where it’s assessed and approved almost instantly.
The next day, Rita’s claim is paid back into her bank account. A message pops up from Sam: “Would you like to transfer the funds to your house savings account?”
Rita’s story is fictional, of course, but most of us would already recognise elements of this as AI technology is already embedded in our increasingly digital lives. And as AI becomes more prevalent, it’s likely to have a substantial impact on the world of EB too.
This is a vast subject, so in this Viewpoint we want to focus on the big questions for multinationals planning for the EB concerns of the future: how AI will help underwriters price risk, handle big data, and motivate your people to lead healthy lifestyles and engage more with their benefits.
What if we could prevent insurance claims before they even happen?
Just as science fiction sometimes predicts reality, we’re already seeing glimpses of how tomorrow’s technology could transform the EB landscape. Health is an area where the impact of AI could be enormous.
Analysts predict the data from wearable fitness devices could be used to help detect potential health issues before they escalate into claims. This could involve the device alerting the user to a habit and suggesting a healthier alternative.1 And these vast data sets could help employers and insurers have a better picture of the potential health claims that could be about to arise.
But experts warn this approach has limits. Privacy laws in many parts of the world already guide how data from personal devices is shared. Would employees be comfortable with a future where their diet and exercise are tracked? And what questions might they have about how the data shared with their insurer or employer?
Multinationals are going to need to consider how to get their employees to overcome questions they may have around data handling. Can they reassure their people that their data is in safe hands so they’re happy to use the tech? If so, they could have access to a potential treasure trove of data.
Just this month, world leaders, technology titans, academics, and other experts came together for the world’s first AI Safety Summit, which took place in the United Kingdom. Privacy and surveillance were among the top items of the agenda on the summit, which opened discussions on how the world should regulate AI, amid concerns of how it could be weaponised or what it could happen if the tech could gain sentience— taking on a ‘mind’ of its own.2
Pricing that changes as your employees do
In other areas, could AI help underwriters make predictions with a level of precision we’ve never seen before? As underwriters use historic claims data to accurately price risks for global employers, could AI help them manage these huge quantities of ever-evolving data?
AI is already being used in shipping to adjust insurance pricing constantly as cargo ships move between potentially dangerous waters where pirates operate and safer seas.3 What if health and life insurance products could evolve with people in real-time, too?
Meeting pricing goals can be challenging amid a backdrop of rising medical inflation.4 AI-powered data analysis could help build a picture of each individual leading to personalised pricing calculations, building in risks that change as their lives do. The detailed employee information could feed into big data sets that help insurers predict population trends more accurately over time, ultimately helping underwriters plot risk more effectively.3
Balancing the portfolio is critical for multinationals managing global EB programmes. And for multinationals using a captive, getting the pricing right will be as vital in the future as it is now.
Nicola Fordham, Chief Underwriting Officer at MAXIS GBN agrees: “There’s a huge opportunity when it comes to pricing EB risks and processing big data. The larger a data set, the more accurately a local insurer and global EB network can analyse the experience used to determine the pricing of policies.
"AI could help to analyse huge data sets even faster and more effectively, so that underwriters can spend less of their valuable time manually sorting data and more time identifying trends and proactively making pricing decisions.”
Faster, better... more accurate?
There’s real potential for AI to be able to inject greater precision into data collection analysis. But could AI still have blind-spots, just like the humans that built it? A general argument for AI involvement in decision-making is that, unlike humans, its cannot be affected by mood, fatigue, or bias. For example, the ‘hungry judge effect’ study revealed magistrates were significantly more lenient towards parole applicants after a meal break and more severe before eating, influencing the widespread introduction of AI-driven algorithms into courtrooms.5
Analysts predict AI could handle insurance claims more rapidly by removing human error, while simultaneously detecting fraud patterns a real person may not otherwise spot.6 But there are still challenges when AI is trained by humans, as it may be programmed with the biases of the creator.
One example of this is relevant in the insurance fraud claims analysis market.7 In some markets there has been criticism of AI “lie detector” style video tools which are trained to detect the facial expressions that suggest someone’s lying. In this case, it has been suggested that the technology could be used to detect fraudulent insurance claims.7
But the science is not being accepted in all markets. Britain’s privacy watchdog has already labelled the concept behind emotion analytics and biometric technologies ‘immature,’ and warned it would likely block their use.8
Living in a chatbot world
It’s clear AI presents ethical challenges for any industry interested in harnessing its powers. But there’s also a window of opportunity for multinationals eager to attract and retain top talent. By embracing AI, multinationals could have even more of their people make the most of their benefits.
As we saw in Rita’s story, chatbots could be a big help in the EB space too. They could provide round-the-clock virtual assistance for questions about health and wellbeing, making the employee benefits journey interactive and bringing it to workers’ fingertips.6
But a word of warning. Many of us can already relate to the frustration of a robotic voice on the end of a phone replacing real people, experts emphasise the importance of offering connections to human helpers too.9
Case study: how AI is already being used in the EB space
Arpit Khemka, SimpleTherapy CEO, explains how his company uses AI to help improve the treatment of musculoskeletal (MSK) pain for employees around the world. He said: “Our programme begins with an AI-driven risk stratification that categorises individuals based on their unique health profiles. This guides the interaction with our clinical team, ensuring a personalised and safe care journey. Using real-time feedback loops, our system dynamically adjusts care plans, keeping the human therapist informed of the patient’s progress and any red flags that may arise.
“It’s also about advancing healthcare equity. Our model is available 24/7, regardless of where you live or work. The people using it may be shift workers, freight truck drivers or warehouse personnel working irregular hours, so our platform is designed to be available whenever they need it, with intelligent reminders for exercise or therapy sessions. This constant accessibility, combined with real-time feedback, accelerates not only diagnosis but also the delivery of appropriate care, making a significant impact in managing chronic MSK conditions.
“Our hybrid model promoting dialogue between AI and human clinicians also ensures that the invaluable ‘human touch’ in healthcare is not lost. Our care team of coaches, physical and behavioural therapists, and doctors, is also available during off-hours such as evenings and weekends.”
Where does AI go from here?
It’s clear that multinationals are already living in an AI world. The question is: where does it go from here?
SimpleTherapy’s Arpit Khemka says: “As we continue to amass valuable data, the horizon holds the promise of deeper insights and more precise care. Our journey reflects a broader narrative of evolving employee benefits. We want to create a future where technology empowers, human expertise guides, and the ultimate beneficiary is the individual receiving care.”
And Nicola Fordham agrees that there’s huge potential for AI when it comes to the global EB space. She said: “AI technology already puts knowledge at your people’s fingertips in their everyday lives. Imagine if they could engage with their employee benefits wherever they are, whenever they choose?
“We already know digital wellness solutions are popular among workers in the war for talent. Products that leverage AI learning to motivate and reward your people for taking charge of their own health and fitness are one of the more obvious solutions.
“But with every new technological leap forward, we must strike the right balance to get the human touch and not become wholly reliant on AI and algorithms.”
Multinational employers, EB networks and insurance companies all have an opportunity to harness AI, while navigating ethical minefields along the way.
It’s clear that the AI ‘future’ is already here. How you use it to meet your people’s needs is a question for today, not tomorrow.
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[1] Balasubramanian, R. et al. McKinsey. March 12, 2021. Insurance 2030: The impact of AI on the future of insurance https://www.mckinsey.com/industries/financial-services/our-insights/insurance-2030-the-impact-of-ai-on-the-future-of-insurance (Sourced: October 2023)
[2] Coulter, M. Reuters. October 31, 2023. UK AI Safety Summit: who will attend and what’s on the agenda? https://www.reuters.com/technology/britains-ai-summit-what-can-it-achieve-2023-10-31/ (Sourced: November 2023)
[3] Anon. Wired. 9 May, 2023. https://www.wired.co.uk/bc/article/how-ai-is-redefining-the-future-of-insurance-microsoft (Sourced: October 2023)
[4] Anon. Aon. 2023. The Global Medical Trends Rate Report 2024. aon.com/en/insights/reports/the-global-medical-trend-rates-report (Sourced: October 2023)
[5] Danziger, S, Levav, J and Avnaim-Pesso. L. Extraneous factors in judicial decisions. 26 April, 2011. Proceedings of the National Academy of Sciences, Volume 108, issue 17. pnas.org/doi/full/10.1073/pnas.1018033108 (Sourced: October 2023)
[6] Anon. Economist Intelligence Unit. September 2023. Why AI matters. https://www.eiu.com/n/campaigns/why-ai-matters-sep-2023/ (Sourced: October 2023)
[7] Bittle, J. 13 March, 2020. MIT Technology Review. Lie Detectors have always been suspect. AI has made the problem worse. https://www.technologyreview.com/2020/03/13/905323/ai-lie-detectors-polygraph-silent-talker-iborderctrl-converus-neuroid/ (Sourced: October 2023)
[8] Lomas, N. Yahoo. 26 October, 2022. UK watchdog warns against AI for emotional analysis, dubs 'immature' biometrics a bias risk https://uk.news.yahoo.com/uk-watchdog-warns-against-ai-115830597.html (Sourced: October 2023)
[9] Source: Tierney, M. et al. Law 360. June 13, 2023. Weighing the risks of AI for employee benefits admin. https://www.law360.com/employment/articles/1687381/weighing-the-risks-of-ai-for-employee-benefits-admin (Sourced: October 2023)
[10] Anon. Vantage Fit. December 18, 2020. 5 Best Ways Rewards For Fitness Can Boost Participation in Employee Wellness Programs https://www.vantagefit.io/blog/rewards-for-fitness/ (Sourced: November 2023)
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The MAXIS Global Benefits Network (“Network”) is a network of locally licensed MAXIS member insurance companies (“Members”) founded by AXA France Vie, Paris, France (“AXA”) and Metropolitan Life Insurance Company, New York, NY (“MLIC”). MAXIS GBN, a Private Limited Company with a share capital of €4,650,000, registered with ORIAS under number 16000513, and with its registered office at 313, Terrasses de l’Arche – 92727 Nanterre Cedex, France, is an insurance and reinsurance intermediary that promotes the Network. MAXIS GBN is jointly owned by affiliates of AXA and MLIC and does not issue policies or provide insurance; such activities are carried out by the Members. MAXIS GBN operates in the UK through its UK establishment with its registered address at 1st Floor, The Monument Building, 11 Monument Street, London EC3R 8AF, Establishment Number BR018216 and in other European countries on a services basis. MAXIS GBN operates in the U.S. through MAXIS Insurance Brokerage Services, Inc., with its registered office located at c/o Katten Muchin Rosenman LLP, 50 Rockefeller Plaza, New York, NY, 10020-1605, a NY licensed insurance broker. MLIC is the only Member licensed to transact insurance business in NY. The other Members are not licensed or authorised to do business in NY and the policies and contracts they issue have not been approved by the NY Superintendent of Financial Services, are not protected by the NY state guaranty fund, and are not subject to all of the laws of NY. MAR01241/0723
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